{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "A notebook for visualizing the outcome of Reinforcement Learning for TSP\n",
    "==============\n",
    "    \n",
    "<font color=#000000 size=3 face=\"黑体\">  This notebook can be used to test and train a pointer network to solve TSP.\n",
    "Structure of networks and function for training and searching is in the package call TSP_pytorch. The version of pytorch used in the packages is 1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import numpy as np\n",
    "import torch.optim as optim\n",
    "import matplotlib.pyplot as plt\n",
    "from TSP_network import *\n",
    "from TSP_train import *\n",
    "from TSP_env import *\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following code use newtwork before training to solve TSP and visualizing the outcome."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean_length_before_training:tensor(29.8057)\n",
      "length_real_of_picture_before_training:[24.086168 21.472664]\n",
      "est_real_of_picture_before_training:[-0.03796547 -0.03751399]\n"
     ]
    },
    {
     "data": {
      "image/png": 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eV0ICcNllTFAY6WgBYBKbjYahJk3s+sGUFG7NCoDSpZmvHuDDv0SJyFoBXLzIVNXOAiAmhi6hcXE0yAYDm40P/LlzmXxrwADP7Rcv5qpEG381gbJ2LbPIDh5M+1ygRIsBGNACwDTffQfs3MmaoMY/1hAA5cp5P371auCmm3KqVkqWjCwBsHu3PU2FMz16MCw+GKsAERqbZ85k8q0hQ7wfM3Ei7RR33239eDT5BxE++C+7jBW/AuXsWXqlRYP6B9ACwBQinJXWqpXTIGl2BXDiBLB9u139YxBpAsDwAHJVB6BsWeCxx4Avv6S3hFUYN+CkSXzwjxzp/ZikJOYB6t0bKKhLGmkCYMECrs5HjeKKPFA2beJqVguAPMSqVUz8NnhwzgeOWQGwZg230SIA3GU+7N+faqJPP7XunCNHssj2gAFMuWtm2Tx5MvW1Tz5p3Tg0+Y+MDGDYMOCqq7jCtQLDABzJNQAc0QLABGPHMiFU9+459xszYW8CID6egqNZs5z7I00AJCVRrVK8uOvPr74auP12ql8yMwM/3+jRdL3r2ZPeVWYe/ufOATNmMA4j2PUKlFLTlVLJSqlEN58rpdSHSqndSqktSqnrgjsijZVMmQLs2kW3T6tWkgkJNP6azQ4cbrQA8MKWLcCPP3KG6uxrnpLCmajh0+8OIwFcsWI595cqFVkCwJUHkDMDBjAl8+LFgZ3rvfdYt/fRRzmjNxt1OXcuva9CZPydCaCdh8/bA6ib/eoFYFIIxqSxgNRU2ptuv91aO5JhAI4WtADwwvjxnBE//XTuz4wYAE8z1/R0JoBzVU6uZMnIcQN1TALniXvvBapXD8wYPHky8NxztKfMmGG+8LyR9+fqq30vz+cPIrIKwAkPTToC+EzIWgBllFJRMvfLnzRqxEjfN97gCn78eOu8dU6f5ipaC4A8wr//Mg3BU0+5TjOckkLD0d9/u+9jwwbqzZ31/0BkqYAOH6YHg7c6wAULcva9YoW9GI4nRPgbNG/O9LozZ7Joyz33ALNn+7b0Xr+effXrFzEudlUA7Hd4fyB7nyYCyczkJGfpUuCddziJuM5Cpd2GDdxqAZBHePddPmiefdb158eO0XUyNtZ9aUfnADBHIkkAePIAcqZnTxZf8bQKSE6mmqdRIxrE1q3jsrtHD6aWmD+f6bR9YeJECtxAsjSGC6VUL6VUglIq4dixY+EeTr7kxAmuyA0nh9WrmV3WqN0bKNFmAAa0AHDL8eP0dnnoIao8XHHwIB/8J04wT70r4uOB2rVdGyxLlmR6iVDl2PGELwKgXDngkUdYhOXkSfv+jAzGS9x3Hw1hzz1Hu8mECUCRIjTg3nILI32NSmpmOX6c+v/HHvNucwkhBwFUc3hfNXtfLkRkqojEikhsBX9KTGkCxlix7trFTL6ffMLYnthYZr09dCiw/hMSmP45mv69WgC44eOPWa/XU1DSkSNcIdSty1WCc/1c5wRwzkRSQrikJM6uzUZCDhjA32f6dFY/ev55qnjuu4+Rlc88wxtu3Toayi9eZBzF99/nNoabYcYMCsu+fX0/NogsAvB4tjfQjQBSReRwuAelcY0hAMqUoQNCz54UBkOHUtVbty7w+uv+1+lOSIiu2T8AQEQi9nX99ddLODh3TqR8eZG773bf5sIFEUDkqqtEli7l3+PH52yzaxf3T57suo9p0/j5P/9YN3Z/adtWxJef+/hxkTp1RAoX5ncoVEjkf/8TWbxYJCPD3u7XX/kZIPL77/6NLStLpHZtkVtu8e94dwBIEA/XH4A5AA4DyAD1+08C6AOgT/bnCsDHAPYA2Aog1lN/EubrOr/Trh2vw/ffz/3Znj0inTvz82rVRL78UsRmM9/3iRM8dvRo68brL96ua8dX2B/ynl7hulE++oi/zKpV7tvMmME2vXvz/T33iJQsKXLkSO42iYmu+/jqK36+datVI/efGjVEHn7Yc5vMTJEffhDp0sX+4AdEevYUOXYsd/vVq0WKFxe59FKRYsV4vD/8+CPPM2eOf8e7w5cbxcqXFgDBxWbLOQkR4ftLLhEpWlQkLc39sb/9JnLddbzebrxRZM0ac+f8+Wce89NP/o/bKny5rrUKyInMTHoING/u2dVw1ixuDfXOO+/Yy8kZxMdzuXnVVa77iJSU0OfP0+PJnf4/KYnZEqtXZ2bQX38F+vShe2uVKjzWORguIYFtL7+cqp/rrzfv7unMxIlAxYqsEaDReGPoUKpX//jDvm/GDBZqadnSs/PBrbfS22zGDF7XzZvT3rV/v/tjgOg0AAPQKwBnvvySknzBAvdtDh4UKVCA7ZYute8fPFhEKZH16/n+qqtE7rrLfT/x8bn7CAcbN3IcX31l35eaKjJ1qkjz5vwsJoarnG++yTmDeuMNfr59u33f5s0iZcuK1KzJpXXRoiLPPeff2P7+m7/piBH+He8J6BVAnmPnTpGCBal2PHuW+86cEalYkdfpxx+b7+vMGZGXXuL1e8klIiNH2vt0plMnqikjAV+ua70CcECyk77Vr89yhO747DMmfAJyznxffpkeAIMG0Wvlr7/cG4CByDECG3WA69YFfvmFbpaVKgG9erFA/LhxnAEtXsxZuOMMqlcvevhMmMD327czXXaxYlwppKZyZdS0qX9jmzqVhvZevQL7jpq8z7lzQMeOXMU//LA9pck779hrWvtS7KVECRqFk5Lo3DBqFF1IHe9/g2iLAP4Ps5LC0wsMl08CsBvAMBefFwEwL/vzdQBqmuk31DMlw5g7bZr7NjabSN26IvXqse3ff+f83DDsDh7M7cqV7vv6+2+2mT7ditH7z8CBHEf16tyWLi3Sp4/IunXmDGFPPEFd/4oVXCmUKSOSlMTPpkxhn7t3+z6uixdFKlQQ6djR92PNAL0CyDPYbLRhGXapuDjuP3SI1+a113J/Sor/54iPF2nWjP3ExtLGJSKSnMx948YF/j2swJfr2oqHfwzoBVEbQGEAmwE0cGrTD8Dk7L+7Aphnpu9Q3yi33y5y+eV88LgjLo6/2gMPcHvmTM7Ps7LoTVOiBJei58657yslhX188IE14/eFs2dFZs4UadnSftO0bUtD6/nzvvWVkMDjW7fmduFC+2dPPUV1kC8eFQaGOm7ZMt+PNYMWAHkHw3HjqqtEqlThfSjC68/wUKtcOfDzZGWJfPGFSNWq9ufAzJn8+9dfA+/fCkItAJoDWObwfjiA4U5tlgFonv13QQApAJS3vkN5o/zxhzkp3qMHH+6DBokUKeL6wbZ6NfuqUsVzX2lpbPfGG/6P2xdsNno2de/O7wCIXHEFb4yWLQPr+4YbOPtv0ybn/saNc+8zy80309XUuJmtRguAvEF8PCdb7drRO+2ZZ7g/MZG2uoEDOWNv3dq6c547J/Laa/Rui4nhveToARhOfLmurbABmMmH8l8bEckEkArARB2t0DFuHEs2eiowfvYsMG8e8OCD1Nu7SwQXG8vslkeOAP/8476/woX5CrYNYP9+4M03qb+89VamYXjgAZZ43LGDevomTQI7R2wsa/o6ek5duMAgMX/0/1u2MFS/b1/zmUI1+Y+jR4EuXRiB27EjgzEffJCfGd5AI0bQNhVosXdHihVjLYudO2kzvOQSc6VhI42Iu7XCkTNl1y7gm2/4sDFcM10xfz4NTT162DOBumLDBhqJChb0Xt4wWPmALlxgdGPbtrw5XnqJkbqzZlEwTZvGh/XBg3QDNZMCwh0ijP6NibEXvwFYHSkryz8BMGkS00V06+b/uDR5m8xMoGtXpiP55htGmVevDtxwAx0QliyhW/bZs7zGjXrcVlKlCiOMjx/33805nFghAMzkQ/mvjVKqIIDSAFwWFpQw5Ex5+22mKxg0yHO76dOZLbN5c88CwEgAN2gQhcZvv7nv08qaACJMvdC3LwtSPPwwZygvvwzs2cMMno8/nrPgi+EB5C0LqCfWrGFCrXbtmGnRCLk3fKN9FQCnTwOff86b20y9ZU3+5MUXgZUrmV68enXgp5+4spXsMqPVqwMDB9qvRytXAM441wqJFqwQAOsB1FVK1VJKFQaNvIuc2iwC8ET2350B/Jqtqwo7R45wVvzEE54rTO3cSZVEjx5U+3gTAFdcwYIT1atTEGRluW5rRU2Aw4eZ17xhQ+DGG/l97r2XLp179wKvvcaEdK7wJQmcO95/nwFvRlm9hx7idv16/qZm8wsZfP45V1ohKvqiiUK++YbXfN++nNQsXMhkhA8+yLrVGzey4lzRosC2bTymQYPwjjkiMWss8PQCcBeAnaA30IjsfaMAdMj+uyiA+aAb6B8AapvpNxTGsuHDGWhkuC16ahcTQ7cyEaY36Ncvdzubja6LTzzB90a6B3f5gFq0ELnjDt/HnZYm8vXXzFdkGKFuuknkk09ETp0y30+/fnT79MdLR4R5jAoUEHn0UZFSpRhwY6TQqF9f5N57fevPZhNp0IBGu2ADbQSOSv76i2lXbrjB7rF3550MxDp3jrl8rrvO7jzw8MN0cc4v+HJdh/zi9+UV7BslNZUPv06dPLfLyKB76D332N8rxchAZ5KS+KtOncr3Nhs9bMqVY8IoZ9q1E2na1PyYN2wQGTCA/QEc17BhIjt2mO/DkVat6NvsLy+8QAFUogQ9dvbt4/7UVP5Go0b51t/KlRKy2AgtAKKPM2fo6lm+vP1aO3aM1+CwYSJjxkgul8xGjTxH5Oc1fLmuI84IHEqmTqUHzNChntv99BNzhRsqjpMnqWd0pQJyLgCjFFUkJ08yktAZM0bgY8eADz4AGjdmBaMpU4BWrVireN8+4K23/NfhG2Ug4+KADz90r6pyxdmz1L8qBVx2GW0M1bKtQRs28DfyVf8/cSJQtqzdk0OjMRBhCuekJNaGMK61BQt43bZtS7XPPfew1i9AQ/FffwVX/x/N5FsBkJ7OilW33+79ITVjBlM8GMWjj2ebr90JgLJlc+rUGzdmWckJE3gxOuJOAGRk2FMvVKnC/PqFCrFOweHDdEdt1y4wz4MzZ+gFdOWVNJYNGkTdu1lee419OD/8Aer/Ad/C4w8fBr79Fuje3b+aAZq8zQcf8LofPZoTIIN58+ji/O23nJSMHWv/bPdu3uvB8ADKC+RbATB7Nmf13tw0U1JY5erRR+05cFJSuHUnAG66Kbfv+uuv0/vm2Wdzlo90FgDbttGDoVo15iOKj2fxla1b+VDt1891fWJ/2LmT2/r17WMwWx5vzRqWzCxSBPj995wPf4BjrVnTN9/oadM4Y+vTx/wxmvxBXBzvi/vuy3nPHj3KyUfr1lyN9uyZ09hrGID1CsA1+VIA2GwM/GrUCLjzTs9tZ8/mbNxQ/wDuBUBKClUqrtJIV6hAr6Bly3KWjyxVil5AEycCzZrxQv3gA7qafvcdcOAAk1kF4wI2PICqVaO3kFLA8uXej1u3jjMwm40utK5KZq5f75v6JzOTqq02bZiUTqMxOHyY7p21awMzZ+YMvvz2W16Hu3ZxMvLaazmPTUxke3cp2fM7+VIALF7Mh9+QIa4jeQ1E6PvftGnOB7A7AfD779y6ywD69NOcbT/7LAO1li0DFi2yf5aWRrXUoUPUa3boQLVPsNixgyuVo0f5Xa+6iq6jnli3jrpWgC6eriKnU1IYAe2LAPj+ewo77fqpcSQjgw//06f5sC9dOufn8+Zxpfnzz7yfnV25ExOBOnWi108/2OQ7ASDZKZ9r1OCF5YmNG5mSwHH2D9gFgHOQUnw8H9ju9N6FCrF27u7dDNRq145/Awyg2rSJuv5QFZVOSuKsat062hLuvZcz99RU1+2Nh3/p0hRggwa5FlBGAJgv+v+JExmpfM89vn8PTd5l6FDG33z6ae5V8KFDDLLMyuL99PzzuY/ftk2rfzyR7wRAfDz1188/z1QNnpg+nYEkXbvm3J+SwhmFs6EyPp4VgZxnG6dP21MvPPUU9509C3zyiT2Pfq1anlcjwcDRA6hJE6B9ey6nV67M3dZ4+FeowBXOJZfYv4sz69fzu5itjrRzJ2dwvXt7/59o8g9ffcUV8YAB9uBCR77+mtv9++02NkfS0nhtaQHgnnwnAMaO5czdeVbvzMWL1P//73+McnXEVRRwWhpnvob6x2azp16oXJnGqeMd6/AFAAAgAElEQVTHef64OKpe1qyxG3RDXRQmK4t60zp1+HC/5RZGERcrllsN5Pjw//prqqcef9x9mob16+lZ5CmvkiOTJ/PB37NnYN9Jk3fYvp336E030c7kirlz6Zhx9dWuc0YlJfE61x5A7slX863EROqaX30192zBmYULWQ3LlaBwJQD+/JNCoF499j9rFvXgpUoBjz3GC/SGG+yz/EGDaNw19OShFgD79lHIFS3K7S230Ih2yy05BYDjw3/FClZDSkuj26grRCgA2rQxN47z5+lm26mT51QcmvzD6dOceJUowVxarmr47t9vTzw4bpxrd2jtAeSdfCUAxo/nDLd/f+9tZ8ygncAIKHHk+PGcAuDcOQZRAVRjKEUvmTffBO6/37UB6qWX+DCdNInvQy0ADA8gQ99veC61akVj2qFDvMkcH/6XXcY4hDvvdJ9X5dAh5lcyq/+fO5eCVht/NQAnEN270zb2yy/u80h99hm3N91EW5orEhO5sqxXLzhjzQvkGxXQ/v1MEvXkk94zTO7bR510t26uc9GnpLCP+HiqLSpXpjdCoULURf7zD49/+GH33gelSzOgZcsWe5+hxMgCuncv1TWG4bl1a26nTs358K9WjbOxw4dpqHaHEQBmxgNIhAKlYUOuPDSad96ht8/YsUDLlu7bffyxfevOdpaYyIe/qxWEOxITec0vXGj+mKjGbM6IcLyszJny7LPMF+Jcw9cVo0aJy3q/IiL794sULcq6twDrjXbrxpxCRgI4s2RlMXEVINKhg2/HBkrv3izVWLasSM+eOcdUujTL6Dnm9rHZmKCtfn3PFbpefJHVmcyUlVy3jt/9448D+y7+Ap0LKKJYsYKJBTt39pyc0CjLet11nvurU4clG32hUSP2/cMPvh0XSfhyXeeLFcCJE5zRdu1Kn2FP2GxU/7RqZW978aI99UKNGnxfujTbHTkCDBtGVYqrADBPbNjA4wGmjw4lO3YwgOvkyZyz7/XrqdKy2VhUw4jw/f13GrkHDfJcoWv9eupczfhdT5pEPe+jjwb2XTTRz8GDzP9Urx697zx5xBn2J0Pt6opz57i69cUAvGQJsHkzPfLatzd/XFRjVlKE42XVTOn11ynVN2/23vbXX9n2iy9YJ7hvX/tsv3p1riQAkQkT7MdMm8Z927ebH9ORIywsXaMGC1YXLWpudWIVlSqJ3Hgjx713L/etXcuUzuXLc79jiuzOnblaOHvWfZ82G9s89ZT386ek8Dv36RPY9wgE6BVARJCWJtK8OVfT3u6h9et5bXor8G60++Ybc2M4d07ksst4zOzZ5o6JVHy5rsP+kPf0suJGOX+e+fnbtzfXvnNnPpgaNOCvU7SoyCOPiPz8M1UfiYncP3eu/Zju3Zme2WxO/fR0kVtvFbnkEqZ33rePf3fp4vv384eTJ/kdGjVi4Xqbzf7wr1OH+fwBkYkT2d7I+T90qOd+d+/mcVOmeB/D22+bF8rBQguAyGDAAF4L8+Z5bmezsQYAIPLGG57bzpyZexLjiSFD2L5sWQqkaEYLAAcmTuS3XLHCfZu0NJFvv2VufpomOTueMiV3cRUjX/3y5fZ99er5Vvikf3/JNdN47TXv47SKtWt5rnLlRLp2zfnw37ePN1r16lyZiIgMHkz7iWEPcMecOex3wwbP7bKyeK6bb7bm+/iLFgDh54sveM0895z3tosX2+9Pb9fi4MEiRYqIZGZ673fTJk5wlKINK9rRAiCbjAxWCWrWzPXsfNMmkUGD7CqP0qW5/eor931+8w3bbNrE98nJfD9mjLkxzZjB9s8/n3P/+fN86F57rbmLNhBmzbLfSIMH53z4G3TvztnQqVP8XR580Hu/zz3HFVN6uud2S5fy3F9+Gdj3CBQzNwqAdgCSwGp2w1x83g3AMQCbsl89vfWpBQDZsoUr31tu8X7NZGTQAaFwYU7OvNG+vUjjxt7bZWby+VCsGAVAKNWwwUILgGzmzpVcesBjx0Q++IAXB8ALqksXkSVLeCFcfbVnVc6UKTzuwAG+X7iQ7+PivI/njz84K2nVihe0M97KR1rF8OGc8RheTM4PfxGuTgBW/AJE1qzx3u+tt5q7OTt0YOlIo5xfuPB2owCIAcuc1gZQGMBmAA2c2nQDMMFTP84vLQA4sbjiCuryDx/23n7yZPuk5YMPvLevVo1lSr3x4Yfyn+onr1QN0wJA+BBv0oTqmYsXRb7/nqUfCxWS/1zIPvqIxkgRkW3buP+ddzz3++abbHfhAt+/8AKFiPHeHUeOUN9es6b9nK7GfOut7stHWsX99/PBD3CF5Go5ffiw/KcmuuEG731mZrLP/v09tzPsCZGw1DYhAJoDWObwfjiA4U5ttADwkawskY4d6S5sZuJ0+jQNtNWr85o8eNBz+1On2O6ttzy327+fpUyNyeCiRea/QyTjiwDIs26gv/zCbJ41a/J1zz3AqlWMAt68makb+ve3B4XNmMGoQW8uiSkpdF0sWpTvV69m1Kvx3hXp6UDnznRHXbjQfSCaUqwFcOKE6/KRVrFxI93kihVj4jfnYi4A0zJUr86oZ0+BXwY7drBPbwFgU6dy26uXz8MOB1UA7Hd4fyB7nzOdlFJblFJfK6Vc/JoaR8aNY62Lt9825zo9fjxTlhcoANx6q/voYIPt27n1lgJiwADmCipZkvfAXXeZG3+ewqykCMfL35mS4Y4IcJbRsaPIggXurfvp6VRJ3H+/974fe4yumyKc9RcuzFWAJ/r141jmzDE3/l69OG5f3ErNsnq1/LeUHjbMc9sGDagXNRPUZdg2PI354kX+zqEOenMHvK8AOgP41OH9Y3Ca7QMoB6BI9t+9Afzqpq9eABIAJFSvXj3UXzViWL6cK8AHHzTnNXfwIPXzhoOGmaDBqVPFbSCnwbffSg4V52uvmf4KEY+369rxlSdXACKsw9upE4uMLFzIUnLuQsJ/+AFITvaeIRTImQguIYGze3cFYAAGtUycyHJ2zmml3fHGG0xW98wzOctHBsq6dTnzptx7r+f2K1YwoZaZoK6EBK6MPBWn//Zb/s5RlPfnIADHGX3V7H3/ISLHRSQt++2nAFwmwRaRqSISKyKxFUJV8CHC2L+f90D9+szvbyb9+ciRLApzxRVcAXTq5P2YxETeP64q1QFMNjdgAHDttby/YmKYIiZfYlZShOMVKl1px44MjHJlmHWmaVORO+/k32PGcPaQnOy67dq1XCG0aWOub0fee499L17s23HuMFw9K1eW/4zfVvo7N2sm0rKl5za33EKDs6dUEqEE3lcABQHsBVALdiNwQ6c2lR3+vh/AWk99Sgiv60ji4kVeIyVLiuzYYe6YLVu4An3mGdryWrUyd1yrVjyXO/r3Z78LFtAmePvt5vqNFrxd146vPLkC8IUjR5gi+vHHzRUjcVwBxMczdN3VhO7IEaa0rVKFGS99LXTiWD4yPd23Y51xTOlsrHKaNvUtSZYn0tNZzcyT/n/rVtZB6NPHcyqJSEJEMgH0B7AMwF8AvhKRbUqpUUqpDtnNBiqltimlNgMYCBqFNU48+yzwxx+s6etplejIkCFMuXLffSzs4q2Cn0Fionv9/7p1TCD39NO8N0VYFyPU2XgjBrOSIhyvUMyUxo/njPivv8y1L1WKsQNZWfSQ6dEjd5u0NJEWLai7DCTS9ccfObZx4/zvwznI6/HH2edLL/nfpzMJCeI1krNvX7rAuvOACgfQgWAhwYjKHTLE/DE//cRj3n6bbssxMXTh9saxY+LWmy89nXE2VaqIpKZyn5GA7pFHzEfyRzq+XNdhf8h7egX7RrHZRK66SuSmm8y1T0vjL/b66zR2AswD5EyfPt4fiGa5+24um834Sjvj/PAXEWnYkGNbujTwsRlMmiQ5cgo5k5pKdztfs6UGGy0Ags/GjQwOvP1282rQzEymKalZk44WtWvb1a7eMCL1ly3L/dnYsfxswYKc+43sv9OnmztHpKMFgEmMlAiffGKu/aFDbD9pEo8Bcuszjf2+zHY8kZREPaXzSmP/fvrUu5u1uHr4izDyUin7DMgKnnzScy6kjz/mb7JunXXntAItAILLiRN8eFepwjgYsxgrhjlz7EndXE20XDFhgriMFdizh9f+ffflPiYzU+SOO/j5tm3mxxmpaAFgkl69qKYx+zDcsoW/2Pz5rAFQvnzOh96aNTSutm1rbTqHwYP50F6/3r6vfXuOpUMHurQ5RtW6e/inpPCYKlWsG5sIl9XuZmg2G1cd118feUtsLQCCR1YWV6+FCon8/rv5486dY5bcpk15vbzwAvswGxjZpw+z9zpeazYb78mSJTlxcsWhQ0waefXVHEOw6d6d92cw8OW6jhJznPWcPw/MmQN06WK+eLlRtcuoBnbTTXZXtsOHafStWpX9uqpR6i8vvUQD7qBBdrfQChVYgWzdOp63UiWWo5wyhfV4HSt5GSQmcnu9S0dF/zh/nq6i7gzAcXH8vF8/c25/mrzB6NHMr//ee0Dz5uaPe/99um4bheC/+ooODGXLmjt+2zYagB2vtTlzgJ9+YonWqlVdH1e5MvDFF7xHzAQ+BsrWrcCePaGvBOhMvhUA33xDy78Z338D45+lFD0HDP//tDT6J58+zZiDSy+1dqxG+cjff+fFDLBgS5UqvFmWLmWk8+ef271snB/+AG8CgDeUVWzcyGhKdwJg4kSgTBnzMRCa6GfZMvrvP/KIbzEfycnAmDFAx46M+F23Dvj3X/PePyK5PYBOnOADvVkz72Np25bFnT75hJ57waR0aW5/+SW45/GK2aVCOF7BXCrffjuXYL6oJYzU0kYBmPh47u/VS7xmEQ2UzEzmL6pShUVZ2rbN7et85gxtBe7K2bVsKaZyqfjC+++77/PwYUY0P/usdeezEmgVkOX8/bfIpZeKXHON5+JBrnj6aXr7GHa1Z56hStU5Jbs7Dh7ktfjRR/Z9PXqwTyN7rzfS0+kUUrKkyK5dvo3fF9q25biefNL6vn25rvPlCmDvXs6Qu3f3TS1x/Di3W7cCRYpQlTJ1Kl/DhlGdFCxiYlgC7+BBFsxOTgYqVszZpkQJYNo09+Xsduyg77+3XCq+sH49+3PV57RpQGYmVyWavM/Fi8x5lZXFqO/ixc0fm5QETJ7MHFFXXskV7vz5vJaN2bI3tm3j1lgB/PYbI/Gffx5o1MhcH4UKcZVdsCBLVKaleT/GH06fpqbg55+tjfb3lYAEgFLqUqXUz0qpXdlbl5o6pVSWUmpT9mtRIOe0gpkz+eB/4gnfjktJob1g7VomgDMSyrVrx/QNwaZFC+Chh5gc6/Dh3ALAEzYbcOwYdZ1Wsn69a/VPZibtEa1bM1hOk/cZMID3xGef+V7jetgwJid89VW+//13e51gsxg2roYN+eDu3Zv1fV95xbexVK/OZ8SGDQxGCwapqbRH7NsH7N4dnHOYIdAVwDAAv4hIXQC/ZL93xQURaZz96uCmTUjIyuI/98473RuE3JGSQqn955/MI9KpEy+WL7+01ujribFjuXW1AvDEli0UAtdcY91YTp1ihKYrAbBkCXO/RFHeH00ATJvG/D4vvgh08PEOj4uj7WzoUPs1PW8eM+zec4/5frZt4/EVKgBvvcVVxaRJFCy+0qEDnS4+/JBjs5pTp4A6dfj3zz9b379ZAhUAHQHMyv57FoD7Auwv6Pz6Kx9M3bv7fmxKChOjZWSwnzNneHGY9VCwgmrV7EniTp82f5xxEbdsad1YNmzg1pUAmDiRRmpvCec00c+ffzK1QuvWvqcxF2GixCpVmC4C4CTt66+Bu+9mqmazGAbgv/6iAHj4YU70nDl71lx/Y8dSzdu9O43RVpKaynu5Ro3oFgCXicjh7L+PALjMTbuiSqkEpdRapVRYhcT06ZzFd+zo+7EpKVRtAJxdzJrlPed4MDCWxYsX82Yxw4oV3N5yi3XjWL+eW2e30l276HHUu7fvOZA00cXx49T7V6zo30r4q6+YI+iNN+wz9bg45tLyRf0jwhVAgwa87ooXpwuqMxMm0Kbw3nvede9FinAlkpVF1WtGhvnxeCIjg+7TZcvSZfvXX+3PlVDjVQAopZYrpRJdvHI8QrOtz+5+0hoiEgvgYQDvK6XqeDhfr2xhkXDs2DFfvotXTpwAFiyge1qRIr4fn5JCPTrApa6Z1LTBwEhctX8/l91m2LyZ2/r1rRvH+vVA7dq5C9xMnswHf8+e1p1LE3lkZbGA0qFDnLEbSRGnTQNeeMH78WlpwPDhVKc+9ph9/7x5FAa+FGjZt48z+9RUCpDx412rSBs25IP/uedoYP77b8/91qlDt9A1a4CXXzY/Hk+kpnJbujQFwOnT9slUyDHrLuTqBRbLrpz9d2UASSaOmQmgs5n+rXaXM8LEN2707/giRXh81arBL9zuia+/lv/KWpopH/nPP2xfqpS146hePXex+HPnWIzngQesPVcwgHYDDYhXXhGXNawrV2aCtZMnPR//zjuSK29PRgYjcp2vK298/z37KlmSZVU9uXd368bo4uLFmf5h/HjveYoMV28rcmjt3s2+Zs5kdL5SzEdkFb5c14GqgBYBMHxpngDwnXMDpVRZpVSR7L/LA2gBYHuA5/WL6dNZKKZxY9+P3bPH7hI2bFjojL6uSE7mdswYrmpee81z+7g4bq30xklO5qzLWf8/bx5w8qQ2/uZ1lizhddetW+7ynu3a0eFg3Dj3x588SbXPnXfmDExcuZKrbF/UP4DdAygtjd5nnty7hwyhGqZ3b87AX3iB13FCgvtj3n+f6t7HHuOKJxAcVwDlygHXXRdGO4BZSeHqBZbD+wXALgDLAVyavT8W2aX0ANwEYCtYTGMrgCfN9m/lTGnTJkrdDz/0/diLF1lg3iilmJRk2bD84tVXOY70dM5MYmI8J7F66inOMnr1sm4MS5ZwDCtX5twfG8tSkpGW98cV0CsAv9izh/l2Gjd2XS508mReG8WKuU8C9/zzvCad06X37MnMsRcu+DamO+7gOV991Vz7Dh24ej57VuSbb+yrlmefZUClK7Zv53e6/fbANAC//sqxrljB90OHMmDy9Gn/+3TEl+s65Be/Ly8rb5RBgxhV6Gs+epuN0YTGw79UqfA/3Pr1Y7SlCKuRlS7NyEJ346pXj2N//33rxvDqq7yBHS/aP/7geSZMsO48wUQLAN85f54P/jJlKAhcYeTyL1CA950ze/fyXuzePef+9HRe14884tuYzp5lf8WL50yK6AmjNrYRNXzqFGtWAFRtLlni+jij9nUgNYSNesQbNvD98uViafU/LQCcuHiR0t4fvbSRyviRR7i9+WZLhhQQnTuL1K9vf++pfKRRIANggRmruPtuzvQd6d6dN6GVqaaDiRYAvmGzUX8OUOfuDkPHfcstfDD/+2/Oz7t2pe79wIGc+40CSIsW+Tau55/ncb7aDW66iTUHHPX/q1fzujb6c67DYbOJPPYYhZsxg/cVQ4gYAvTCBdZMGDjQv/6c0QLAifnz/XsArlrFpdndd9vzAA0ebMmQAuLWW/kySE+nQLjiitx1fhcutAuAv/+25vw2m0jFijkLvBw/zou4d29rzhEKtADwjSlTeB2NHOm5XXo6H5ADB1IA9Oxp/2zdOnFbka5bN65mzc7iRejQERPDPmfMMH+ciMh338l/dQccSUtj0afChbnS+eSTnHWsz5zhqrpyZff1wD1h5M86fty+r21bFqeyAi0AnLjrLiZR80Vvt38/H3J169KboWdP8TrzCRX163MV4Ii78pHPP88bpEgR64qx79snuZJuGR4dZpNuRQJaAJjnjz/4QLzzTnP3UY0aXDUPHMjrb+dOThxuuYX3lbO+++JFPvx9qRqXmcm6AaVL89pzrJdhhqws3ktNmrhWn+7YYU+geOutOcvGbtrEe6p9e9/vK8OG57jyMErTOq+K/EELAAcOHOBsZMQI88dcuMALq2RJGn5ERNq04a/lzkAUSi69lHYAZ1yVj2zWjG6Z115r3fm/+Ya/xdq1fJ+VxdVHixbWnSMUaAFgjmPHRKpV40PdrA3tttuoYjlyhIbThx6yr0YnTcrdfvFifuYuk60rPviAx3TuzK2v2UdF7Jl9f/rJ9ec2G9uULUsB+Npr9hWKoRXwtWb3s89SVeqI4aQyc6bv38EZLQAcGD2a39JsaldHPefChTk/O3o04OEETHq6uPV2cC4fefYsVVhlyljrlz9sGPs1PDWWLeOYZs+27hyhQAsA72RmirRuzdluQoL543r0EKlUiX8PH87ro2ZNzrhd+dw/+igfsunp5vrft4/eQnfeyWu7dm3zY3Pk4kWqclq39tzuyBEKMYCqmrg4Pis6d+a94EvVsx49clfly8riyshXA7grtADIxmbjzNRRX+6Njz4SU3rOcGHUJZ440fXnjuUjDe8CpUReftm6MbRqxSA0g44dGbzji+42EtACwDsvvshr6NNPfTvu9dd53LlzDFQsWlTcGngvXODK1Zfc+B070pC8dy9Ljnbo4Nv4HDGKxf/5p/e2P/zAlRDA8pP//EPBVr26+bKVnTrldqAQoYC57LLAvQx9ua7zdD2A+HimWjVb9WvVKiakuvde31PIhgojCMxdJlDH8pGrVrE6mIh1KSBEGDATG8v3+/YxJ1HPnv6l19BELosWsRJdz57Ak0/6dmzt2tz+8w+DJo3AyfLlc7f98UemNzEb/LVgAfDdd0wdXaUK83I1bOjb+Bzp3Ztp3seP9962fXsGnT33HOuANG/O4w8e5G8kJnL7nzrlusZBmzbA0aOsNxIyzEqKcLwCnSl1785lohnd4L59nMVeeaX5CkThwPCxXrXKfZtPP2Wbhg1FatUyP7sxw86d7O+TT/h+xAiuMP75x5r+Qwn0CsAtu3Yx5uX6630PyhIRWbNG/nOaGDGCf5cty4AtZ7p25b3nLR2DCO/Nyy8XadSI6qLERLFE/ThkCG2F7mIbXJGQYA8QbdhQcjlGuCM2lsZjZ/bvZx9vv21+DK7w5brOsyuAM2eYabBrV++ViS5cYGH1ixeZNtlsBaJw4G0FADA8v0kTYPt2e4Iuq9JAGEmrmjYF0tOZKOuee5jWVpM3OH+e90PBgkzyVrSo733UqsXtn38C77zD1MyvvMLMl451cM+f5wqyUydzmWNHjGAxpKlTWb3LSAERaFbeQYO4Snn3XfPHXH89M5m+/TaTysXEMFW7t8RuqamunzFVq3Klvny5b2MPhDwrAObPB86d8573XwTo25dqjS++sDZbZjAwIwBiYliGUYRpdatWZblIK1i/njURGjZk2b/kZJ33Jy8hQpVGYiLTO9es6V8/FSsyo+e8ecwL9Oab7LdaNT7EDVXJkiW8T80Ufl+7lnUm+vdnkXeAKaBjYlhGMhAuv5x5fqZPt2f8NUPBgiw5mZjIQvZZWUy5vmaN+2PcqYAAqoF++y14pSidybMCYMYMXhTNm3tu99FHzOv/6qu+VzIKB8nJvOjKlPHczkgZvW+ftbPzhASuLgoWZLWl2rVzJvPSRDeTJnEi9NprroupmEUplh/dvh0YOJCCpGhRYORIYN06zvoBrtIrVeLD0xMZGUw6d/nlOcuvJiYCdetaY38aPJjagI8/9v3YWrW4shk5kg/vFi2YNPLChdxtU1Pd379t2vCY33/3fQx+YVZXFI6Xv7rSpCTq0saO9dxuxQoGqXTsaF2QVLDp0YM6UG907EjvBCBn2ohAyMigT/fAgSJbt4pfPtCRBLQNIAdr1tCN+O67rbkfypfn/eXoHZOezuDKa65hypBLLhHp3997X2PGiEvX7Lp16VVjFR072pPE+YvhOQWI1Kkj8vPP9s8uXOD+0aNdH3v6NH+z4cP9P78v13WeXAHMmMFloWORCWf27QO6dOHs4bPP6C0TDRw75r0WsM0GrF4N3HYbPRumTbPm3H/9RZ1t06acKRYp4l9pTU3kkZzMyl7VqgGffx74/bBsGQsoxcTknO0WKsSykVu3UhV04YJ39c+ePVyh339/zkp+Fy7wMyur8g0Zwipn06f738eoUUCrVkDhwly5tGkDPPEEfw/HVNCuKFkSuPHGEKaHNispwvHyZ6aUkcHAjnvucd/m/Hn6sZcqxXDvaOKGG5g3xBPbtnGWMX26tec2oib//JPeVY8/bm3/oQYmZkoA2oGFj3YDGObi8yIA5mV/vg5ATW99RtoKICODKY6LFvW/WJIjmZmc4Zcrx+vl2LGcn2dlMTK9eHGuZj2tNmw2RuGXLJk7TcKGDex//vzAx+xIixb09TfjleSOw4cZ2FW/Pj2MChbk72HEHHjyWjIy7fqaudjAzHVtvKJk3muen36il4A733/JNnJt2EBdZ6DGo1CTnOx9BWAUgLGy/i9A/X+pUjRwnT2b942/SqkYAB8DaA+gAYCHlFINnJo9CeCkiFwB4D0AY0M7ysAZMYI1oydP9q9YkjOzZnGGb8QO7N2b8/MCBVhS9dw54KqrPK82vvySs+HRo+nz74jhARRIDIArhgxhEfj58/3vo1IlYPZsxigcPw5s3Ehtw9Ch/NyVbcCgTRs+p4w63kHFrKQIx8ufmVKnTvQpds6KaWBk4rOyBFsoKV5c5LnnPLd55BGG4VtdtyA2ljPFq6/mCircdRECBV5mSgCaA1jm8H44gOFObZYBaJ79d0EAKQCUp34jaQVg5HXq08ea/s6e5az+xhtFtmwRl9k2RURmzeJnFSu6jzNISeG9fMMNrhPQDR3K/Dxm00eYJSuL6R4aNw78GjfsAbNns9/nnuPs3lPm0owMaif8LeDk7bp2fIX9Ie/p5euNkpxMI5a7B+Svv9LAct990WP0deTsWf7Hxozx3K5GjdzZQgPl4kX+tkY+FF9TA0QiJgRAZ2RXtst+/xiACU5tEgFUdXi/B0B5F331ApAAIKF69eqh/qou2bGDqpVmzaxL42GkgFi92n69ujJ43jckPM4AABpCSURBVH03H/4A61m4ont3qk6cq4Y59mFlkkNHpk/n2BzrFftDRgZVSiVKMIhSxJyBuWNHBnH6gy8CIE+pgGbPptHFlWHy339pbKpXL7qMvo4Y/smeVED79/O7Wq3+2bKFv+2+fTRgPfSQtf3ndURkqojEikhsBSM6L4ycPcvgqyJFqOqwwo3y6FFg7FgGkbVowQDMihVzq4BOnqSq9vHHaSwdPZrjcWTlSjpzPP88cO21rs+XmGi9+sfg4YfpcuqprrEZChYE5syhQfiBBxhs6i0wFaAa6O+/aeQOJlH4GHSNCC33TZvm9go4f54eBBkZjPQtWTI8YwwUIwjM0/MjmPp/gD7c3bszyCcfcBBANYf3VbP3uWyjlCoIoDSA4yEZnZ+IAE89Ra+uOXOA6tWt6ffVV/mAGzPGvq92bT7IHFm4kPfigw8yQOzYMeCDD+yfX7xIO12tWvSrd8WZM5zoWOkB5EiRIozq/eUXRjMHQrVqwMyZwKZNLEBvhtatuQ26N5DZpUI4Xr6ogBISxGWucZuNOnGlIqOYSyAYOdPXrXPfpk8f6g8DKVrtiu7dGQMARJ/nlDvgXQVUEMBeALUAFAawGUBDpzZPA5ic/XdXAF956lP8UG1ajZFH350vuj9s3071qrNP/0MP5VZl3Hkn0zcb+vUOHVjUxaiQNXKkd/XL2rVs89131n0HZ06d4r3ka6lJdzz7LMf87bfe29psrMHgT4yDt+va8RX2h7ynly83Sr9+dGM7eTLn/nff5bd8/XXTXUUshhump9KODRuKtGtn/bmvvpq/r7e86dGEmRsFwF0AdoK6/RHZ+0YB6JD9d1EA80E30D8A1PbWZzgFQFwc9epWBz/eey8fls4lEkeMoGAwXCpTUvh+2DB7m82bOUEbNoyCpFAh73nxjYSHu3db9x1cMXQok8RZcZ60NDpSlCljrjxrjx5MoOfrZC7fCYDz5/mjPvxwzv3Ll/Of97//RafR15m33hKPlY9SUvj5m29ae96zZ/k7AvQaySv4cqNY+QqXADh8mDEyV1xhbcbblSt5bbz1Vu7PjAf13r18P3Uq3zvHGzz0EKOCmzVjxTtvxZeefZbtg31fHzxITyNXFfj8Yc8eCsobb/TuvTRnjnhd8bvCl+s6T9gAFi5kgiVH3/9//qGOsX596t+i0ejrTHIyDUjujEjx8dxarf/fsIHRxZdeGh35kjS5MXTup04xiZ9VGW9tNubQqVaNGTWdMeoCGHaAefPoD9+oUc52r71G3f8ffzB63Vusi2EADvZ97W+SOHfUrg18+ikT2730kue2rVpxG0w7QB54LNJboEYN4Pbb+d4w+mZmRrfR1xlvQWBxcfQ2aNrU2vMuXcptjx7mUvZqIo9hw1gg6JNPgGuusa7fuXPpIPDmm8wS64whAPbupZfQihUURErlbFeyJNNEKAXccYf38wbTA8iZwYMpnCZMsKa/Ll2YrXfcOBbDcUeFCky8qAWAB/79l/mzu3e3V7/q2RPYvJkeDnXrhnuE1uFNAKxezYe/P/nbPfHtt9w++6y1/WpCw/z5zHPfvz/wyCPW9XvxIiN6mzRx32/Vqpw0/P03ryObzXXlL+PaKlgQeP11z+c9cYLR/sHyAHKmfn3mIJowgdHLVvDuu3RvffxxVhNzR5s2zAzq7CZrFVEvAGbN4kP/iSf4/t13+eB/4w2Wb8tLeBIA589zJma1+keyawpUqcLlsCa6+OsvTo6aN2dhFiuZMIETsPHj3atiYmK4Ot+7l+qfBg1yP7h//JEriREjgKefpso2Kcn9ebdt4zZUAgBgCocTJ6xLrHjJJfw9zp+n8MzKct2udWuq7wz3bssxaywIx8ubsSwriymPW7Xi+59+orGyc+foT1PgisqV3RfO/vVXGoyWLLH+vDab3UUvL4E8bgQ+fZrJyCpWZLlBK0lJoevmXXd5b9u6NUsnKsVEZ46cPcvI9fr1GY189CjTnTzwgPv+Jk3itb5vX0BfwWduvpnF361MPWGkxHjlFdefnz8vUqQIjd5m8eW6juoVwG+/0djboweXmF27coYxY0ZuHWO0Y7N5TgUdF8fvfNNN1p9bKRqANdGDCO+LXbs406xa1dr+33iDwVhmImVr1+Y4RHKrf159lauIqVMZfFWxIgOwvvqKgVOuSExkUkKrv5M3hgxhJHwgSeKcefxxai9GjWK5TGcuuYSr+qDZAcxKinC8vM2UHn2Us5Bjx5gTpEyZ4PsFh4vjx8Vj3pTWrVkoW2Me5OEVQM+eErSCPbt301e/Z09z7Q335YYNc+7fuJExAc79nDzJe/nuu13317KlSPPmPg87YLKyRBo04H1mpYbhzBmRK69kAkdX7q9GCulDh8z158t1HbUrgNRUFqzu2pXGra1bqfuvUyfcIwsOnmoBZ2YyRbPV+n9NdDJhAl0Nr7iCHixWM3y4vbCLGUqV4tbw0gOo837qKaB8+dyriDJlONtesiR3aUQRrgBCqf83KFCAqRw2b2YuI6soUYIrnpMnuSKw2XJ+3qYNt8EoFh+1AmDuXHohFC7MJe7o0UC7duEeVfDwJAA2bqR3ghYAeQMRPhg7dgR27/bt2Nmz6Y/fpAndPq1Wha5dSxXICy+w5q8ZLrmE92nLlvZ9EybQaeH994GyZXMfM3Agr/UXX7QXkAd4Hxw/Hh4BAFiXJM6Za69lPqRly2hUd6RRI7qEBkUNZHapEI6Xp6XyDTfQAKyUSJcuedPo68j8+VwGukqNa6S7OHgw9OOKZhChKqB//uH/Uylub7pJZPLknLV1XfH553SCuP32wGrausNmY2rjSpWotvD1WIN9+5geuV07z/fthx/y+//0k33f8uXct3y5b+e3kvHjOYb1663t12aj8TsmRiQ+PudnXbvSCcTMc86X6zoqVwDbtjEr5dGjnAlMn573jL7OeFoBxMXR0KbdNPMGZ85wO2EC0yufOsXAocqVmVL4++/pGujIF1/QmNiyJT83k3LYVxYsYLT5qFFUW/iCcX+K2N0eJ070fN/26sVMpSNG2FcB4XABdTWuUqVyz9QDRSkaw2vUYLr1Eyfsn7VuzdiH7dutPWdAAkAp1UUptU0pZVNKxXpo104plaSU2q2UGhbIOQH+SACXlQsX+n4xRiOGAChfPud+EQaAafVP3mH/fm4bN6YuPDGRKYl792Yk7b330gPm2Wep/vv885wP/2Ck6s7IYDRxgwau622Y4cAB4OabOWF58EGme/ZEkSLAK68A69cD333HfYmJvAe8pYoIJqVKAX370gZpdb7+0qWp3jbK2hqCz7ADWK4GMrtUcPUCcBWAKwGsBBDrpk0MmEmxNuwpdRuY6d/VUjktjX6xVlTriSb69mVRaWf++kvyTIWuUIMIVQFNmSJu/dzT00UWLWKa4MKF2Q5ggrdgesB99JH4HWeSkSHyzjtU+xQpwvTPZlVIGRki9erRgygzk94/LVv6PgarOXSIv3/fvsHp/733+Ht/8IF9X7165uIufLmuLbmgvQgAr3VV3b1c3SjDhnHU3bp5/yHyEp06sU6pM0Z2xaSk0I8p2olUAeCcQtkdRkBUqVLcFihAvfqXX4qcO+fbb+GJU6c4+bjjDt9tbfHxdNEG+PAysoL6wty5PP7zz/ldn37a9z6CQc+eTJHuLXOpP9hsTLFdqBBrnYjwexcv7r7euYEv13UobABVAOx3eH8ge59fvPoql6KGGii/4C4NRFwc9+elnEf5nf37ac/xlHjv88+Bfv2YOO3wYaZOePFF6ogffhioVIk5sVatyu1W6CtjxtDzZvx487a248fp5tmiBXXZ335L9ZQ3tY8runShJ8yIEcDp0+HV/zsyeDCQlmZdkjhHlGJA62WXUV12+jTVQOfO0eXbMrxJCADLwcLXzq+ODm1Wwv0KwGthbaf2EVc8OxK48kp6OzlTs6Z/VYM0kbsCuO02ev6447PP6CHUqlXumX5WlsiKFazgVqIEZ841a4q8/LLIrl2mfpYc/PsvZ7mPPWaufVYWCxeVK8dVzODBvnsMueL77+U/ddeqVYH3ZxX33ceiLVZ8R1fExfF3fPBBBsjFxIi89JLnY3y5ri25oL0IAEtVQPmVsmVzL3337+d/8P33wzOmaCdSBUCdOnT7c4Wnh78z586JfPGFSNu29oI+Zl1KDR57jHr7f//13nbLFrqJAtxu2WLuHGaw2ZgzCBA5cMC6fgPl99+Dfw+++SbPMXUqbSA33OC5faQJAK91Vd29tAAgaWn8T732Ws79RsUgQ0eo8Y1IFABZWXzgvvBC7s9mzTL/8HfmwAGmFGjQgNdMkSJcUS5e7D652Z9/8nxDh3ru+8wZzvRjYjjznz49OJW63nqLaRhSU63vOxBuucX6JHGOZGWJtGnDlVifPhTmngR4yAQAgPtBnX4agKPGTB/A5QB+cGiXq66qmZcWAOTgQf6nnAve9+vHZb43Y6HGNZEoAI4c4f/6o49y7jce/q1bB2bgtdn4YB80SKRCBZ6rYkWRZ54R2bDBbuS12Wj0LVfOfflIm40lQqtWZT89ezJLaH5j8WJ+/y++CN45jhwRuewy+yrIU2nWkK8AgvXSAoBs3Oj6n37NNVzea/wjEgXA+vX8Xy9caN9n1cPfGcOltHNnu0vp1Vcz0vWzz/j+ww9dH7tnD716AHr5OEeu5ieMJHHXXhvcjARGFHShQlwJuMOX6zoqI4HzG66igE+eZFCMDgDLW+zbx2316tzOmgV068b6sN99Z22QV6FCDCqbP5+eRJMmsTTjCy8wKVmxYkzMdv68/Zi0NJZ/bNiQHkbvvMMgtWCkIY8WjCRxW7Ywl0+waNWKdYQzMuxV+gJFC4AowChG7SgA4uPpE6EFQN7CiAK+/HJgyhRG3bZqBSxaFJwIX4NLL2W6id9/t5dkLF6cgqBSJeDJJ4H33mPSspdeAu65h9XGnntO14kG6HpbpYr1SeKceeUVpn1JTgZ++SXw/rQAiAJcrQDi4jiDa9YsPGPSBIf9+1nTecIEPpCbNuXD31XB9WBw9izw8cf03z98GFi5Erj7buCzz/iw37uXeWpGjw59QZZIpnBhpuZYsYKpK4JFwYKMD7j8cmvyn2kBEAUkJ/NhX7q0fV9cHB8OoXowaELDvn1U/+zcyYfK0qWh/R+/8w5rQBuJzhITWbNXKeC++4DbbmP69Xr1KCSmTKE6UsPAt9KlrU8S58ytt7KQ/B13BN6XFgBRgBEFbEj8CxeCUwBeE36MKOAffgAee8x1rvxgcfgwVRhdunDCceONLLYUG0tBsGABk5Ht28d2qanes5TmJ4wkcd9843sdh3ChBUAU4JwG4o8/eKPdfHP4xqQJDvv20bZz9izw6KOhPfcrrwDp6czC2awZs3fOmcOHfr169nZVqtDouXUrDcB9+lBVdO+9/OyZZ5ilVMTtqfIsAwdSTfPOO+EeiTm0AIgCkpNZEcjAKADfokX4xqSxnowMzsIPHaJ+/dZbQ3fuxESWkSxcGPjyS878d+xgyVV3umalgOuuY1Wvgwdpq2jZkt5E111Hg/H48fw++YXKlZmae8YM1iuJdLQAiAKcVwBxcUyIFUr1gCb4HDrEWfPevfQqKRCiu9NmY71eEeDKK7nC/PDDnDYnb7hzKR0yBKhWjeVav/wyp0tpXuX557mSCkaSOKvRAiAKcBQAmZl01dP6/+CilLpUKfWzUmpX9taluFVKZSmlNmW/FgVyTiMGICuLVbNCSePGzDq5fj1w/fWB9eXoUrpzJ7OU7tjB72S4lP72W+BZSiOVK6+kwfzjj6nKi2S0AIhwzp3jrMkQAJs386LSAiDoDAPwi4jUBfBL9ntXXBCRxtmvDoGc0IgBqFeP6pNQUaAA9fxz5wIxMdb2Xbcu4wr27qWdoHNn4Kuv6E1Upw4wciSwa5e154wEhgyhd9Snn4Z7JJ7RAiDCcY4BiIvjVguAoNMRwKzsv2cBuC/YJ9y4kdtQG39DQYECtA9Mn07d+OzZFHRvvpk3XUpvvJE2nHffjWzPKC0AIhxXAqBWLXpbaILKZSJyOPvvIwAuc9OuqFIqQSm1VinlVkgopXplt0s4ZoR2O7FqFbfduvk95qigWDHaOJYty9supUOGcFU3b164R+IeLQAiHEcBIEIBoGf/llFPKZXo4tXRsVF2gi13To01RCQWwMMA3ldK1XHVSESmikisiMRWcHTpcqBgQf6fq1UL4BtFGXnZpbR9e+ZMGjcucsevBUCE4ygAdu1iXiDt/28ZO0Xkahev7wAcVUpVBoDsbbKrDkTkYPZ2L1gXo4m/g4mPZxRufiQvupQaSeK2bg1ukrhA0AIgwjEEQIUKWv8fYhYBeCL77ycAfOfcQClVVilVJPvv8gBaANgeyEmtyO8S7Ti6lB45Et0upQ89xJiOsWPDPRLXaAEQ4SQnAyVKUG8aF0dBcOWV4R5VvmAMgDZKqV0AWme/h1IqVill+HZcBSBBKbUZwAoAY0QkIAGgyUnZsjldSkeMiC6XUiNJ3MqVjK+INLQAiHAcYwDi4qj+0bPE4CMix0WklYjUFZHWInIie3+CiPTM/vt3EblGRBplb6eFd9R5m7p1gVGj7C6lXbpwlRDpLqWhShLnD1oARDiGADh0iBe+Vv9o8juGS+m0aVQRzZ7NVbHhUnrTTZHlUlqyJNCvX2QmidMCIMIxBIDW/2s0uTFcSpcupcvluHHA6dNUG1WqxFXC4sXhdykdOJC2jbffDu84nNECIMJxFADFizNkX6PR5Obyy+1eNxs2MDXzb78BHTrYXUo3bAiPS2alSkwSN3NmZCWJ0wIggrHZ6PZpCIDmzXX5PY3GG0oBTZrYXUoXL7a7lF5/ffhcSgcPZpK4jz4K7Xk9oQVABHPyJBODlSjBWY1W/2g0vlGoEOsXGy6lkyeHz6W0Xj3g/vsjK0mcFgARjBEDcPKkLgCv0QRK2bJA797uXUp79Ai+S+mQIcCpU8AnnwTvHL6gBUAEYwiA/fs5k7nhhvCOR6PJK7hyKf36a7qU1q4NvPxycFxKb7ghspLEaQEQwRgCICmJustixcI7Ho0mr+HKpbR+fWD0aLtL6eTJ1rqUDh3Kcptz51rXp79oARDBGAJg2zat/tFogo07l9K+fa11KW3fnhX9IiFJnBYAEYwhANLTtQDQaEJJMF1KlWLfiYkUNuFEC4AIJjnZrvbRBeA1mtATLJfSrl0jI0mcFgARTHIyL8CGDVlnVaPRhA9XLqWlSvnnUmokifvtN2DduuCP3R1aAEQwR48CFy9q9Y9GE2kYLqXx8f67lD71FFCmTHiTxGkBEMHs389AMC0ANJrIxV+XUiNJ3Lffhi+LqRYAEYxROlYLAI0m8vHHpXTAAKqDwpUkLiABoJTqopTappSyKaViPbT7Rym1VSm1SSmVEMg58wvp6cCFC1wi5qcasRpNXsDZpXT8eODMmdwupeXKMUncrFnhKQca6AogEcD/AKwy0fZ2EWmcXUBb4wVj9q+rf2k00c3llzMR3JYtdB3t1y+nS+nFi0BaGvDhh6EfW0ACQET+EpEkqwajsZOQvU5q4neJcY1GE0kYLqXvvWd3Kb3tNntE8NixFBKhJFQ2AAHwk1LqT6VUrxCdM6opUICzg7vuCvdINBqN1RgupV99RdXP0KFM+16qVGjH4TW7vFJqOYBKLj4aISLfmTzPzSJyUClVEcDPSqkdIuJSbZQtIHoBQPXq1U12n/e4916+NBpN3qZsWWDMGL5CjVcBICKtAz2JiBzM3iYrpRYAaAY3dgMRmQpgKgDExsaGOVOGRqPR5F2CrgJSShVXSpU0/gbQFjQeazQajSaMBOoGer9S6gCA5gCWKKWWZe+/XCn1Q3azywCsVkptBvAHgCUiEuYUSBqNRqMJqMKsiCwAsMDF/kMA7sr+ey+ARoGcR6PRaDTWoyOBNRqNJp+iBYBGo9HkU7QA0Gg0mnyKFgAajUaTT1ES7qKUHlBKHQNwDkBKGIdRPh+fP69/9xoiUiGI/bsk+7r+12TzcP8PzKLHaS2BjNP0dR3RAgAAlFIJ4Uwgl5/Pn5+/e6QQLb+BHqe1hGqcWgWk0Wg0+RQtADQajSafEg0CYKo+f748dyScPxKIlt9Aj9NaQjLOiLcBaDQajSY4RMMKQKPRaDRBICoEgFJqvFJqh1Jqi1JqgVKqTIjPb6r2scXnbKeUSlJK7VZKDQvFOR3OPV0playUCnnWVqVUNaXUCqXU9uzffFCoxxBphPv6N0s47hNfCOc9ZZZQ33tRIQAA/AzgahG5FsBOAMNDfH5fah8HjFIqBsDHANoDaADgIaVUg1CcO5uZANqF8HyOZAJ4XkQaALgRwNMh/u6RSLivf7OE9D7xhQi4p8wyEyG896JCAIjITyKSmf12LYCqIT5/qGsfNwOwW0T2ikg6gLkAOobq5NnV2k6E6nxO5z4sIhuy/z4D4C8AVcIxlkgh3Ne/WSK8RnhY7ymzhPreiwoB4EQPAD+GexBBpgqA/Q7vDyAfPgSVUjUBNAGwLrwjiSjyw/UfDPQ95YKA6gFYiZnaw0qpEaCKYHY4zq8JHUqpEgC+AfCMiJwO93iCTbivf7Po+yRvETECwFvtYaVUNwD3AGglQfBdtaL2sYUcBFDN4X3V7H35AqVUIfDhP1tEvg33eEJBuK9/s0TYfeIL+fqeckdUqICUUu0ADAHQQUTOh3s8IWA9gLpKqVpKqcIAugJYFOYxhQSllAIwDcBfIvJuuMcTCeTD6z8Y5Nt7yhNRIQAATABQEsDPSqlNSqnJoTy5u9rHwSLb4NcfwDLQCPqViGwL5jkdUUrNAbAGwJVKqQNKqSdDdW4ALQA8BuCO7P/1JqXUXSE8fyQS1uvfLKG+T3wh3PeUWUJ97+lIYI1Go8mnRMsKQKPRaDQWowWARqPR5FO0ANBoNJp8ihYAGo1Gk0/RAkCj0WjyKVoAaDQaTT5FCwCNRqPJp2gBoNFoNPmU/wN9P59ZOttccQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ptr_net=Ptr_Net(hidden_size=128, embedding_size=128,dropout_p=0)\n",
    "critic_net=Critic_Net()\n",
    "ptr_net.apply(weights_init)\n",
    "critic_net.apply(weights_init)\n",
    "points=get_point(100,20,2)\n",
    "#data visualization before training\n",
    "roads=ptr_net.get_road(points)\n",
    "print('mean_length_before_training:'+str(torch.mean(get_length_sum(points,roads))))\n",
    "print('length_real_of_picture_before_training:'+str(get_length_sum(points,roads).numpy()[0:2]))\n",
    "print('est_real_of_picture_before_training:'+str(critic_net(points).detach().numpy()[0:2]))\n",
    "draw(points,roads)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the followiing code load a network trained after 10000 iter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "ptr_net_trained=torch.load('train_deacy_ptr9.pkl')\n",
    "critic_net_trained=torch.load('train_deacy_critic9.pkl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see the outcome after training by the following code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean_length_before_training:tensor(19.0244)\n",
      "length_real_of_picture_before_training:[15.587549 19.403425]\n",
      "est_real_of_picture_before_training:[16.274183 17.163214]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 7,  5, 10, 16,  6, 19, 18,  3, 12, 14, 17, 13,  1,  2,  0, 15,\n",
       "        11,  8,  4,  9],\n",
       "       [14,  9, 16,  7, 17, 15, 13,  1, 10,  8, 12,  0,  3,  4,  5,  2,\n",
       "        18, 19,  6, 11]])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "roads=ptr_net_trained.get_road(points)\n",
    "print('mean_length_before_training:'+str(torch.mean(get_length_sum(points,roads))))\n",
    "print('length_real_of_picture_before_training:'+str(get_length_sum(points,roads).numpy()[0:2]))\n",
    "print('est_real_of_picture_before_training:'+str(critic_net_trained(points).detach().numpy()[0:2]))\n",
    "draw(points[0:2,:,:],roads[0:2,:])\n",
    "roads[0:2,]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "you can also trained the network by yourself. TSP_train.py provide two function for training. Training train the network with constant learning rate and learning_rate_adjusting_train train the network with decaying learning rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ptr_net2,critic_net2=training(ptr_net,critic_net,batch=128,city=20,coors=2,lr_c = 0.001,lr_p = 0.001,beta1=0.9,\n",
    "                    n_baseine_gradient_steps=1,train_steps=1000,show_i_time=10,show_j_time=10,show_j=False,\n",
    "                            print_training_log=True,log_file_name='train_log_constant.csv')\n",
    "ptr_net3,critic_net3=learning_rate_adjusting_train(ptr_net,critic_net,batch=128,city=20,coors=2,lr_c_init = 0.001\n",
    "               ,lr_p_init = 0.001,beta1=0.9,n_baseline_gradient_steps=1,\n",
    "               train_steps_per_iter=1000,train_iter=10,decay=0.99,\n",
    "               log_file_name='train_log_decaying')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the following code is the 'Active Search' part in the paper. It use policy gradient to guide the searching. This searching can be used to both pre-trained network and untrain-network. The following code show active search with untrain-network.(In the original paper, it do such kind of searching for 10000 iterations)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "10\n",
      "20\n",
      "30\n",
      "40\n",
      "50\n",
      "60\n",
      "70\n",
      "80\n",
      "90\n",
      "14.521962143480778\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "point=points[0]\n",
    "ptr_net4=active_search(ptr_net,point,batch_size=128,plot_comp=True,plot_mean=True,save_name='search1_',\n",
    "              log_file_name='search_log.csv',iter_time=100)['ptr_net']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the following code is the 'Active Search' part in the paper. It use policy gradient to guide the searching. This searching can be used to both pre-trained network and untrain-network. The following code show active search with trained network.(In the original paper, it do such kind of searching for 10000 iterations)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "10\n",
      "20\n",
      "30\n",
      "40\n",
      "50\n",
      "60\n",
      "70\n",
      "80\n",
      "90\n",
      "13.479944609105587\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ptr_net5=active_search(ptr_net_trained,point,batch_size=128,plot_comp=True,plot_mean=True,save_name='search1_train_',\n",
    "              log_file_name='search_train_log.csv',iter_time=100)['ptr_net']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "we can compare the solution with the optimal one"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12.754250191152096\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "('good', 12.754250191152096)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "road_opt=opt_road(point)\n",
    "(draw(point,road_opt),get_length_sum(point,road_opt))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Due to the limitation of devices ,I can only train the network for TSP20. But I can test it on TSP50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean_length_before_training:tensor(58.0391)\n",
      "length_real_of_picture_before_training:[57.87213  47.549053]\n",
      "est_real_of_picture_before_training:[0.02464712 0.02477493]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ptr_net50=Ptr_Net(hidden_size=128, embedding_size=128,dropout_p=0)\n",
    "critic_net50=Critic_Net()\n",
    "ptr_net50.apply(weights_init)\n",
    "critic_net50.apply(weights_init)\n",
    "points50=get_point(100,50,2)\n",
    "#data visualization before training\n",
    "roads50=ptr_net.get_road(points50)\n",
    "print('mean_length_before_training:'+str(torch.mean(get_length_sum(points50,roads50))))\n",
    "print('length_real_of_picture_before_training:'+str(get_length_sum(points50,roads50).numpy()[0:2]))\n",
    "print('est_real_of_picture_before_training:'+str(critic_net50(points50).detach().numpy()[0:2]))\n",
    "draw(points50,roads50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean_length_before_training:tensor(58.8187)\n",
      "length_real_of_picture_before_training:[66.45384  48.983013]\n",
      "est_real_of_picture_before_training:[19.3288   17.549955]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 0, 41,  6,  1, 35,  4, 28, 20, 24, 31, 29, 47, 38, 18, 44, 49,\n",
       "         2, 33, 32, 46, 15, 34,  3,  8, 21, 37, 16, 25, 14, 48, 13, 45,\n",
       "        10,  9, 27, 22, 19, 11, 43, 17, 30,  7, 12, 36, 26,  5, 23, 40,\n",
       "        39, 42],\n",
       "       [ 0, 34, 38, 31, 20,  6,  1, 41, 39, 14, 32, 12, 30, 37, 21, 48,\n",
       "         5,  9, 27, 44, 24,  7, 42,  8, 13, 26, 17, 49, 25, 43, 16, 23,\n",
       "        29, 40,  2, 10,  4, 11, 28, 18, 33, 19, 46, 36, 47, 15, 22, 45,\n",
       "        35,  3]])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "roads50=ptr_net_trained.get_road(points50)\n",
    "print('mean_length_before_training:'+str(torch.mean(get_length_sum(points50,roads50))))\n",
    "print('length_real_of_picture_before_training:'+str(get_length_sum(points50,roads50).numpy()[0:2]))\n",
    "print('est_real_of_picture_before_training:'+str(critic_net_trained(points50).detach().numpy()[0:2]))\n",
    "draw(points50[0:2,:,:],roads50[0:2,:])\n",
    "roads50[0:2,]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
